Future of an Ageing Population

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Future of an Ageing Population | Health and Care Systems Men Percentage of men in ‘not good’ general health (%) 50 40 30 20 10 0 Country: Wales 0 1-19 20-49 50 or more Amount of unpaid care provided (hours per week) England Women Percentage of women in ‘not good’ general health (%) 50 40 30 20 10 0 0 1-19 20-49 50 or more Amount of unpaid care provided (hours per week) Country: Wales England Survey of 16,723 people Figure 6.5: Percentage of males and females with ‘Not Good’ general health by extent of unpaid care provision they provide per week in England and in Wales, 2011 140 . Policy Implication Demand for people to provide care for family and friends will increase. Supporting these carers, and addressing the health and employment outcomes associated with providing unpaid care, will be critical to ensuring this demand is met sustainably. P84
6.4 Medical and assistive technologies Technology is likely to play an increasingly important role in providing health and care support, and in connecting people. This may include the mainstreaming of technology-enabled care services, for example home health monitoring tools, the use of social media to create and sustain online communities with shared interests and the increasing and more sophisticated use of health data to improve clinical treatments 177 . The rapid evolution of medical and assistive technologies makes predicting the scale of their impact difficult 186 . The speed of development also creates a need for new methods of evaluation of these technologies 177 . While technologies that assist in health and care could be significant contributors to the growth in expenditures in these sectors in the short term, they could potentially reduce costs significantly in the medium and long-terms. These savings will depend on the type of technology, for example whether they treat symptoms, prevent disease, change behaviour, radically innovate or incrementally improve, and how they are implemented 187,188 . Developments such as 3D-printed joints and organs, therapeutic robotics and genomics have great potential to improve health outcomes across the population 189 , while improvements in personalised (‘precision’) and stratified medicine may allow better targeting of medicines, making treatments more cost-effective 190 . Increases in real-time data collection, driven by developments in wearable technology and other forms of telemonitoring, will enable healthcare professionals to provide more appropriate treatment and support for patients and carers 191 while the resulting large datasets could drive forward research in many areas and potentially help improve prevention and early intervention 177 . Technology such as alarms, home monitoring systems and GPS locators can help carers locate people with dementia, although ethical issues can arise. There is evidence that carers are already using off the shelf technologies such as baby monitors and smartphone-based GPS tracking apps in supporting people living with dementia 192 , but specialised technology could be more widely and effectively used. To capitalise on the advances in assistive technology, a number of barriers will need to be overcome, those being common to all technologies (see Chapter 7) and some specific to assistive technologies. As with many new technologies, cost can be a barrier to their implementation. The use of telecare to improve social and health care for vulnerable older people was judged not yet cost-effective when assessed 193,194 , and the commissioning of technology could be inhibited because the public service provider might not benefit directly from the potential savings 195 . Local authorities could fund care-assisting technologies but the NHS would gain benefits through, for example, reductions in hospital admissions. P85
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Future of an Ageing Population P1
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Foreword People in the UK are livin
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The Government Office for Science w
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Learning and training will become o
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across different socio-economic gro
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Priorities include: • Adapting he
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Box A: Perceptions of youth and old
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• Keating, N , Kwan, D., Hillcoat
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Population ageing refers to a chang
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70 95 Life expectancy at birth (yea
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Increased life expectancy is the re
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Work Population ageing, combined wi
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Box 1.3: Pension landscape People w
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2.1 Longer working lives Working la
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100 80 Employment rate (%) 60 40 20
Page 33 and 34: However, there is evidence that the
Page 35 and 36: Country Turkey Denmark Bulgaria Cyp
Page 37 and 38: 50 Percentage of people (%) 40 30 2
Page 39 and 40: Box 2.1: Special circumstances rela
Page 41 and 42: and learning faced by older people.
Page 43 and 44: 3.1 Lifelong learning to enhance me
Page 45 and 46: and numerical skills. People withou
Page 47 and 48: smaller proportion of men of any ag
Page 49 and 50: Policy Implication Participation in
Page 51 and 52: 4.1 Changing demand for housing In
Page 53 and 54: 30 Number of homes built (thousands
Page 55 and 56: younger people who commit to provid
Page 57 and 58: 4.3 The importance of the wider nei
Page 59 and 60: International Case Study: De Hogewe
Page 61 and 62: 5 Number of people (millions) 4 3 2
Page 63 and 64: Policy Implication Many of today’
Page 65 and 66: 5.1 Family trends occurring in para
Page 67 and 68: 100 90 80 Unweighted data Weighted
Page 69 and 70: In general, evidence suggests that
Page 71 and 72: 5.4 The impact of ageing and ‘ver
Page 73 and 74: Age (years) 65+ Care receipt 2007 2
Page 75 and 76: approach overlooks interdependencie
Page 77 and 78: 6.1 Changing health and care needs
Page 79 and 80: Social isolation affects 7-17% of o
Page 81 and 82: transfer of care into the community
Page 83: combine health and social care skil
Page 87 and 88: can apply for benefits. Application
Page 89 and 90: 7.1 Benefits of connectivity Connec
Page 91 and 92: Travel habits change over the life
Page 93 and 94: Policy Implication Different age gr
Page 95 and 96: 100 Proportion of respondents who u
Page 97 and 98: Percentage of internet non-users (T
Page 99 and 100: Policy Implication Virtual connecti
Page 101 and 102: The response to an ageing populatio
Page 103 and 104: ced impact ess, including rm condit
Page 105 and 106: Term Accredited training Age struct
Page 107 and 108: Morbidity rate Multi-morbidity Non-
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Page 111 and 112: 1 DWP (2011) Predictors of attitude
Page 113 and 114: 36 ONS (2016) Regional labour marke
Page 115 and 116: 71 Eurostat (2014) Table: Individua
Page 117 and 118: 107 Sugiyama, T. and Ward Thompson,
Page 119 and 120: 147 Harper, S. (2016), Population A
Page 121 and 122: 183 O’Reilly, D. et al. (2015) Ca
Page 123 and 124: 219 Burton, E. and Mitchell, L. (20
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Future of an Ageing Population

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